Understanding the structure and evolution of flow fields within wind farms is essential to properly plan wind farms and estimate wind turbine and farm efficiency. Turbine wakes maintain wind speed deficits relative to the free stream flow and enhanced turbulence capable of providing higher dynamic loads to downwind turbines. Although only a few observational studies on the impact of turbine wakes exist, initial findings suggest power output decreases for individual wake-influenced turbines can reach 40%. Total power output loss due to wake influences across a large wind farm can be as large as 20%. [1] The character of turbine wakes directly relates to appropriate turbine spacing and associated infrastructure costs. Accurately forecasting the expected total power output of a large wind park on short temporal scales requires a full understanding of the complex modulated flow fields within the wind farm itself.
A multitude of numeric simulations (LES, CFD, etc.) has been conducted in an attempt to quantify the structure and effect of turbine wakes. Reference [1] (Barthelmie et. al.) listed below provides a detailed list of concerns when applying these simulation results to the real atmosphere and full-scale turbine systems. Among other limitations, current numeric simulations are not yet capable of accurately handling the natural variability of atmospheric stability and turbulence as well as complex underlying terrain. The net result is a systematic underprediction of wake losses within a large wind farm. Additionally, the computational expense of accurately incorporating turbine and blade geometry into simulations remains large, requiring the employment of simplified approaches that do not exactly represent reality. [3] Despite these limitations, wake modeling efforts are necessary as current observational capabilities are not yet able to provide the spatial and temporal resolution needed to document the full range of scales within a turbine wake in the real atmosphere. However, to validate the simulation results, expansion of existing observational capabilities and coverage is vital.
To date, observational studies of the horizontal influence of turbine wakes are limited to sparse tower, sodar, and/or LIDAR measurements. Fixed meteorological tower measurements provide valuable “ground truth” data but are inherently limited in their horizontal and vertical coverage. Sodar is limited in its ability to document flow fields beyond time averaged vertical wind profiles of horizontal wind speeds. Scanning and staring LIDAR systems can provide for quantification of the flow fields (including inflow and wake flow) but are limited with respect to range, range resolution and temporal revisit times relative to radar technology. Existing LIDAR technologies also do not provide information during periods of precipitation, and have exhibited less reliability for long-term field deployments.
Existing published wake studies indicate that current LIDAR technology is handcuffed by the inverse relationship between maximum range and along-beam range resolution. This limitation precludes the ability to fully observe wakes of significant length or wake interaction over the footprint of a large wind farm using current LIDAR technology. The maximum presented along-beam range gate spacing from scanning LIDAR wake studies is 30 m [4] using the National Oceanic and Atmospheric Administration (NOAA) High-Resolution Doppler LIDAR [5].
Accordingly there is a need for an apparatus and method to more accurately evaluate wind flow upstream, downstream and/or within wind farms to provide better optimization of wind farm layouts and operations.